bert-base-cased-fine-tuned-sst2

This model is a fine-tuned version of bert-base-cased on nyu-mll/glue sst2 dataset. It achieves the following results on the evaluation set:

• Loss: 0.4606
• Accuracy: 0.9209

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 2e-05
• train_batch_size: 16
• eval_batch_size: 8
• seed: 42
• optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.1111	1.0	4210	0.3592	0.9106
0.0726	2.0	8420	0.4517	0.9106
0.0396	3.0	12630	0.4606	0.9209

Framework versions

• Transformers 4.46.3
• Pytorch 2.5.1+cu121
• Datasets 3.1.0
• Tokenizers 0.20.3